An Initial Approach for Learning Objects from Experience

Report No. ARL-TR-8356
Authors: Troy Dale Kelley, Sean Michael McGhee, Jonathan Milton
Date/Pages: May 2018; 34 pages
Abstract: The US Army Research Laboratory's Vehicle Technology Directorate (VTD) and the Human Research and Engineering Directorate, as part of VTD's 6.1 refresh program, have initiated a program called Adaptive Perception Processes for Learning from Experience (APPLE). The program's goal is to develop a set of perception capabilities that are sufficient to enable continuous object learning, where new object instances and categories can be learned from experience in an open-set framework. We have shown preliminary results from initial tests using a motion detection algorithm to delineate objects, which are then fed to a simple feed-forward neural network without any other processes in the pipeline. Our neural network trains to an asymptote of acceptable performance and our topology can be defined using our nonparametric model. ARL will continue research to determine the best algorithms to use in the pipeline for the APPLE program.
Distribution: Approved for public release
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Last Update / Reviewed: May 1, 2018